Model Analysis Method Research Articles

MEDIATING EFFECT OF VIDEO-ON-DEMAND ON XXI’S CUSTOMER PERCEIVED VALUE AND LOYALTY

Disruption has become the main reason for abandoning conventional ways of modernization. This phenomenon also applies to the entertainment industry, where cinemas compete with subscription video-on-demand (SVOD). The largest cinema industry in Indonesia, Cinema XXI, is undoubtedly not resistant to this disruption. This research study applies a sample of 215 respondents from the sliced population of Cinema XXI customers and SVOD services subscribers. It aims to review the mediating effect of subscription video-on-demand services on the relationship between customer perceived value and customer loyalty to Cinema XXI. This study is a quantitative research, applying the Structural Equation Modeling (SEM) analysis method. Primary data was taken directly from the respondents using a Google Form-based questionnaire and later analyzed using JASP software. The results of the study show that subscription videos on demand do not have a significant mediating effect on the relationship between customer perceived value and customer loyalty. Subscription video on demand does not have a significant effect on customer loyalty. Though without a mediation, customer perceived value directly affects customer loyalty and subscription video on demand.

Sufficiency and necessity of big data capabilities for decision performance in the public sector

PurposeThis study aims to examine the necessity effects of big data analytics capabilities (BDAC) on decision-making performance (DMP), particularly in the public sector.Design/methodology/approachThe authors used the combined methods of partial least square structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) to test the hypothesized relationships.FindingsThe findings show that the presence of all three BDAC (infrastructure, management and personnel) is significant and necessary to achieve higher levels of DMP. Specifically, the results revealed big data management capabilities to be of higher necessity to achieve the highest possible DMP. The findings provide public-sector practitioners with insights to support the development of their BDAC.Originality/valueTime-sensitive domains such as the public sector require insight and quality decision-making to create public value and achieve competitive advantage. This study examined BDAC in light of the combined methods of (PLS-SEM) and NCA to test the hypothesized relationships in the public sector context.

ANALISIS STRATEGI PENGELOLAAN DESTINASI WISATA TAMAN WISATA ALAM MANGROVE ANGKE KAPUK SEBAGAI DESTINASI EKOWISATA DI KOTA JAKARTA UTARA GUNA MENINGKATKAN MINAT BERKUNJUNG KEMBALI

The purpose of this research is to find out how the management strategy is applied in the Angke Kapuk Mangrove Nature Park area to increase interest in visiting again. This research method uses a descriptive qualitative research method. Data collection techniques used by researchers using primary data and secondary data, primary data includes interviews, observation, and documentation. The analytical method used by researchers is an interactive model analysis method from Milles, Huberman, and Saldana which includes data condensation, data presentation, and drawing conclusions. In conducting an in-depth analysis, the researcher used theoretical triangulation and data source triangulation methods to strengthen the results of the study. The research results from the author's interviews with tourists also show that there is an influence on the intention to return. There is a relationship between the dimensions of interest in repeat visits and ecotourism variables such as attractiveness, accessibility and facilities and other factors that can be linked back to the main variable, namely management strategy. Suggestions from the results of this activity the Angke Kapuk Mangrove Natural Tourism Park area can continue to improve the management activities implemented in the mangrove forest area by continuing to support the concept of ecotourism.

Effects of COVID-19 vaccination programs on EU carbon price forecasts: Evidence from explainable machine learning

The COVID-19 pandemic continues to destroy the carbon market. To alleviate the situation, governments launched vaccination program campaigns. This study aims to predict two carbon pricing features––return and volatility––considering the impacts of the COVID-19 vaccination program. The present study applies the SHAPley Additive exPlanations method of model analysis and interpretability to determine the forces that predict carbon pricing. Our results show that compared with the volatility of the carbon market, the number of daily vaccinations has better predictive performance in terms of carbon pricing. However, compared with other related control factors, the predictive contribution of the COVID-19 vaccination program to volatility is greater than the return of the carbon market. In addition, a smaller number of daily vaccinations correspond to higher carbon market volatility and lower returns. Our results have crucial implications for investors and policymakers in stabilizing and promoting the carbon market during the COVID-19 pandemic; moreover, our results provide a reference for formulating new COVID-19 vaccination-related policies.

The Impact of The Development of Conversational AI on The Stock Indexes of Relevant Industries in The Chinese Stock Market

In recent years, the AI industry has been booming and has been favored by many investors. In 2023, generative AI has received a lot of attention due to the release of chat GPT, which has changed people's lives while also having a lot of impact on the stock market, In this paper, we will use the time series model and multivariate statistical analysis method to measure the impact on chat GPT on the stock price of related industries.

E-Service Quality, Online Customer Reviews, and Purchase Intention as the Moderating Role of Purchase Decision

The existence of technology has caused a change in people’s spending patterns, where initially, shopping was carried out in person, but now it can be done online. To increase the number of buyers, increasing the e-service quality for online sellers is necessary. This research will examine the influence of e-service quality, online customer reviews, and purchase intention as the moderating role of purchase decisions. This research will be carried out using a quantitative approach. The data analysis method used is the Structural Equation Model (SEM) analysis method with SmartPLS3 software. This research then finds that e-service quality and online customer reviews significantly affect purchase intention. Then purchase intention has a significant effect on the purchase decision. Lastly, e-service quality and online customer reviews affect purchase intention, which affects purchase decisions.

RELATIONSHIP BETWEEN SAFETY CULTURE AND THE SAFETY CLIMATE, SAFETY BEHAVIOR AND SAFETY MANAGEMENT

This article aims to measure the application of occupational safety and health using Cooper's Reciprocal Safety Culture Model and Confirmatory Factor Analysis method. The objective function of this article is to find out the aspects of safety culture that have been implemented by companies. A questionnaire was circulated to staff on the company's production floor as part of this study. The results of the questionnaire recapitulation were then analyzed using the confirmatory factor analysis method. Based on the score calculation results and the category determination build on the questionnaire scores on each dimension of the safety culture applied to the Steel Company, the safety climate value of 55.58 is obtained, which is on a 'quite good' scale. The safety behaviour value of 44, 89 is included on a 'quite good' scale, the safety management system value of 22.04 is on a 'poor' scale, and the safety culture value of 40.83 is on the 'quite good' scale. With these results, it is essential to make improvements to the safety culture in the company, especially in the dimensions of the safety management system, which is on the 'quite good' scale.

Study on Dynamic Model Construction and Analysis Method of Bacteria-algae Co-culture

To investigate the dynamic changes in growth and product synthesis of a mixed culture of Rhodotorula glutinis and Chlorella vulgaris, this study utilized fermentation data to analyze the rules and preliminary results of the microbial-algal symbiotic system. Employing Matlab, the author fitted a mathematical model proposed by predecessors, seeking parameters to establish a dynamic model for microbial fermentation. This model not only characterized parameter significance but also shed light on interactions, energy transfer mechanisms, and natural regulation balance during symbiotic fermentation. Results revealed that, under the influence of algae's photosynthetic carbon fixation, bacteria exhibited secondary growth, coupled with lipid synthesis and cell growth. The mixed culture model demonstrated a significant increase of 25.9% in biomass and 42.1% in oil content (reaching 30.694 g/L and 14.54 g/L, respectively). These findings suggest the model's potential as a theoretical guide for optimizing mixed culture fermentation processes.

Mediating effect of e-learning quality on learning outcomes through student satisfaction in nursing education

Abstract Objective This study aimed to determine the relationships between e-learning quality, student satisfaction, and learning outcomes and the mediating effect of student satisfaction. Methods A cross-sectional quantitative correlational study using a predictive design and multivariate analysis method was employed in this study. A sample of 241 nursing students were recruited through an online survey based on a stratified random sampling technique. The variance-based Partial Least Squares Structural Modeling analysis method was used to test the possible relationship and mediating effect among the variables. Results The findings revealed statistically significant relationships between e-learning quality, student satisfaction, and learning outcomes. A mediating effect of 37.2% is predicted for e-learning quality on learning outcomes through student satisfaction. Conclusions This study emphasizes the learning needs of working nurses and the impact on their learning outcomes in e-learning nursing undergraduate programs. Advances in e-learning education have assisted nurses to be more self-sufficient in their pursuit of lifelong learning.

Моделирование энергетического приемника для систем сверхширокополосной хаотической радиосвязи

The problem of modeling an energy receiver of ultra-wideband chaotic radio pulses for chaotic radio communications is studied. As is shown, a combination of numerical and analytical modeling completes the problem of calculating characteristics of ultra-wideband chaotic communication systems. On the one hand, the numerical method is effective for calculating receiving systems with short radio pulses, and with an increase in the duration of radio pulses Tp the rate of the method decreases proportionally, whereas technical requirements for the computing equipment increase proportionally, so the operation time increases faster than Tp. On the other hand, the accuracy of the analytical solution, which is insufficient in the case of short radio pulses, grows proportion-ally with an increase in the duration of the radio pulses. Thus, in this problem, the numerical and analytical methods ideally complement each other. It is shown that the accuracy of the approximate analytical solution for the optimal threshold and the error probability becomes sufficient for engineering calculations at the values of the number of freedom degrees (processing gain) of chaotic radio pulses B  200. The combination of numerical and analytical modeling methods can significantly simplify tiresome modelling of chaotic communication systems, for example, those that provide maximum range by increasing the signal length.

Strategic Management Analysis of Haidilao

In recent years, with the economic and social development, the development momentum of the catering industry continues to be hot, and at the same time people's consumerism and other major changes are also taking place. And in 2020 China's catering industry by the impact of the new crown virus, the development of a serious obstacle, the competition is more intense. The development strategy of catering industry enterprises has become a problem that deserves attention. As a successful model in the catering industry, Haidilao Company enjoys a high reputation among the crowd, but it also faces some development difficulties. This paper takes Haidilao Co., Ltd. as the research object, firstly introduces Haidilao's company profile and current development strategy, and analyzes the enterprise's strategic management method using Porter's Five Forces model and SWOT analysis method. Finally, according to the analysis of the content of this paper puts forward to promote product innovation, strengthen the diversification of development, strengthen the quality management and strengthen the construction of corporate culture and talent training and other recommendations, hoping to provide a certain reference for the Haidilao or catering industry practitioners.

Investigation of MEMS Single Turn Meander-Shaped Silicon Carbide Piezoresistive Pressure Sensor on a Clamped Circular Diaphragm for High Pressure Harsh Environment Applications

Silicon-based Microelectromechanical System (MEMS) pressure sensors are extensively used and have the advantages of high accuracy and miniaturization. Despite this, due to inherent material limitations, they are not easily able to withstand high temperatures greater than 150°C. To overcome this disadvantage, Silicon Carbide (SiC) is the preferred material because it has excellent thermomechanical properties and operates above 600°C. Piezoresistive pressure sensors made of Silicon Carbide are ideally able to detect pressures beyond 600°C. Our work presents MEMS Single turn meander-shaped piezoresistive pressure sensor on a circular SiC diaphragm for high pressure applications of pressure range 0–40[Formula: see text]MPa in harsh environment. This work models and analyses the piezoresistive pressure sensor characteristics using an analytical modeling and simulation method to choose the best design. To ascertain its sensitivity, expressions are computationally simulated with MATLAB software using the thin plate and small deflection theory. To evaluate the viability of the model, COMSOL Multiphysics simulation is used. When compared to recent studies, our proposed sensor provides a sensitivity of near about 5.4[Formula: see text]mV/V/MPa across a pressure range of 0–40[Formula: see text]MPa.

Workplace Harassment And Perception Of Organizational Support On Turnover Intention: Job Satisfaction As A Mediation Variable

Purpose-This study looks at job satisfaction as a mediating variable to explore the relationship between workplace harassment and perceived of organizational support on intention to leave. Design/Methodology/Approach-Employees in the textile and textile products sector in Central Java Province made up the study's population. Purposive sampling was used to acquire the data for this study, and a total of 60 participants made up the sample. Through the use of an analytical program called Smart PLS version 3.0, the outer model and inner model analysis methods were used to analyze the data for this study. Findings-The direct findings demonstrated that job satisfaction and turnover intention were highly impacted by workplace harassment and perceptions of organizational support. Job satisfaction did, however, have a negative and negligible effect on the intention to leave. The indirect findings indicated that there was no evidence to support the idea that job satisfaction could moderate the effects of workplace harassment on intention to leave and the perception of organizational support on intention to leave. Research limitations/implications-These findings have policy implications for all levels of government in Central Java Province, which must prioritize reducing workplace harassment through strict enforcement of regulations. For companies, the results of this research can be used to develop perceived organizational support programs. Originality/value-The study on employee behaviour in the textile products business is quite restricted, and no earlier studies on the influence of workplace harassment and perceived organizational support on turnover intention mediated by job satisfaction have been done. This study also calls into question the widely held belief that findings collected in one specific location may be extended to the larger phenomena at the country level.

State-of-health estimation for lithium-ion batteries based on Bi-LSTM-AM and LLE feature extraction

With the increasing demands for battery safety management, data-driven method becomes a promising solution for highly accurate battery state of health (SOH) estimation. However, the data-driven method faces problems of poor interpretability and high dependence on input features. This paper proposes a SOH estimation method that integrates data-driven model and signal analysis method. Specifically, the differential thermal voltammetry (DTV) analysis method is used to analyze aging characteristics to obtain features strongly related to battery aging and solve the problem of poor interpretability of data-driven methods. The use of local linear embedding method (LLE) for feature extraction has improved model efficiency. A data-driven model is constructed with the Bi-directional long short-term memory (Bi-LSTM) as the core, and the attention mechanism (AM) is added to focus on important parts of the sequence to further improve the accuracy of the model. The proposed method is validated based on the Oxford battery degradation dataset, and the results show that the proposed method achieves high accuracy and strong robustness in SOH estimation with a root mean square error (RMSE) maintained at about 0.4%. This method has the potential to be employed on cloud platforms or end-cloud collaboration systems for online implementation.

Quantifying economic sectoral iron commodity use and related vulnerability in China's supply chains

With its widespread use in manufacturing and machinery, iron is a crucial metal for modern society. However, knowledge about the economic vulnerability of iron from multiple perspectives remains unexplored, especially for China, a country responsible for more than half of global iron and steel consumption. This study aims to quantify the inter-sectoral flows of iron commodities and the caused economic vulnerabilities, using an input-output model and complex network analysis methods. Results show that the residential building construction sector was the most vulnerable sector from a direct perspective. However, the final uses of certain services (e.g., the public administration and social organizations sector and business services sector) were more vulnerable concerning supply restriction from a consumption-based perspective. Based on the above findings, policy recommendations, such as circular economy and material substitutions are proposed to help improve resource efficiency and reduce the vulnerability of critical sectors from dependence on iron and steel.

The Classification Impact of Different Types of Environmental Regulation on Chinese Provincial Carbon Emission Efficiency

The evaluation of inter-provincial carbon emission efficiency and the analysis of its influencing factors hold great practical significance for reducing carbon emissions and promoting sustainable development in ecological management. To address the shortcomings of existing research in the classification evaluation of carbon emission efficiency and account for the impacts of different environmental regulatory policies on carbon emissions, this paper aims to examine the impact of formal and informal environmental regulations on carbon emission efficiency. This is accomplished by utilizing a combination of the data envelopment analysis (DEA) model, entropy weighting, and k-means cluster analysis methods. The fixed-effects model is also applied to examine the influences of different factors on carbon emission efficiency under different categories. To conduct the case studies, carbon emission management data from 30 provinces in China are collected, and the results show the following: (1) Formal environmental regulations exhibit a “U-shaped” relationship with carbon emission efficiency, whereas informal environmental regulations have an “inverted U-shaped” relationship with carbon emission efficiency. (2) Under the cluster analysis of carbon emission efficiency, formal environmental regulations are found to have a stronger incentive effect on inter-provincial carbon efficiency compared to informal environmental regulations. This study carries significant theoretical and practical implications for China’s timely attainment of its double-carbon target.

Pengaruh Suku Bunga, Jumlah Uang Beredar dan Nilai Tukar Rupiah Terhadap Tingkat Inflasi Provinsi Sumatera Utara Tahun 2012-2021

This study aims to analyze the effect between variables both partially and simultaneously on interest rates, amount of money in circulation and exchange rates on the inflation rate in North Sumatra Province in 2012-2021. This research is a research using a quantitative approach. The independent variables in this study are interest rates, money supply and exchange rates. While the dependent variable in this study is inflation. Secondary data collection techniques with quantitative research types obtained from Bank Indonesia, the Central Bureau of Statistics and from related agency sources. This study uses the Error Correction Model (ECM) analysis method. The results showed that the interest rate variable had a positive and signifikan effect on the inflation rate in the long term, whereas in the short term the interest rate had a positive but not signifikan effect on the inflation rate. The money supply variable has a positive and insignifikan effect on the inflation rate in the long and short term. Meanwhile, the exchange rate variable has a negative and insignifikan effect on the inflation rate both in the long term and in the short term.

Calculation of the change in raw cotton mass when passing through the working chamber of the harvester

The motion of the mass of a cotton plant through the working area formed by two parallel spindles on paired drums refers to the class of problems on the material passage through a narrowing area. The article is devoted to modeling the interaction process between the spindle apparatus and the cotton plant to determine the change in the mass of the cotton product (raw cotton) with plant elements when passing through the working area of the harvesting apparatus. According to this model, a cotton plant is modeled as a continuous medium with the simplest mechanical property characterizing the process of compression and tension of the cotton mass. To perform numerical calculations, classical methods of modeling and probabilistic analysis of technological processes of interaction between cotton and the spindles of a harvesting machine were used. On the basis of numerical calculations, in the MathCAD 15 programming environment graphs were plotted that describe the patterns of changes in the cotton mass during the contact of cotton with the spindles of the cotton harvester.

Modeling of spatial spread of COVID-19 pandemic waves in Russia using a kinetic-advection model

Objectives. COVID-19 has a number of specific characteristics that distinguish it from past pandemics. In addition to the high infection rate, the high spread rate is due to the increased mobility of contemporary populations. The aim of the present work is to construct a mathematical model for the spread of the pandemic and identify patterns under the assumption that Moscow comprises the main source of viral infection in Russia. For this purpose, a twoparameter kinetic model describing the spatial spread of the epidemic is developed. The parameters are determined using theoretical constructions alongside statistical vehicle movement and population density data from various countries, additionally taking into account the development of the first wave on the examples of Russia, Italy and Chile with verification of values obtained from subsequent epidemic waves. This paper studies the development of epidemic events in Russia, starting from the third and including the most recent fifth and sixth waves. Our twoparameter model is based on a kinetic equation. The investigated possibility of predicting the spatial spread of the virus according to the time lag of reaching the peak of infections in Russia as a whole as compared to Moscow is connected with geographical features: in Russia, as in some other countries, the main source of infection can be identified. Moscow represents such a source in Russia due to serving as the largest transport hub in the country.Methods. Mathematical modeling and data analysis methods are used.Results. A predicted time lag between peaks of daily infections in Russia and Moscow is confirmed. Identified invariant parameters for COVID-19 epidemic waves can be used to predict the spread of the disease. The checks were carried out for the wave sequence for which predictions were made about the development of infection for Russia and when the recession following peak would occur. These forecasts for all waves were confirmed from the third to the last sixth waves to confirm the found pattern, which can be important for predicting future events.Conclusions. The confirmed forecasts for the timing and rate of the recession can be used to make good predictions about the fifth and sixth waves of infection of the Omicron variant of the COVID-19 virus. Earlier predictions were confirmed by the statistical data.

Mitigation synergy and policy implications in urban transport sector: a case study of Xiamen, China

The urban transport sector is one of most significant contributors to greenhouse gas (GHG) and air pollutant (AP) emissions. To achieve co-benefits of GHG and AP emission reductions, a synergistic mitigation approach targeting both climate change and air pollution has gained more attention. In this study, we evaluate mitigation synergy and policy implications for GHGs and nine APs, namely, sulfur dioxide (SO2), nitrogen oxides (NO x ), carbon monoxide (CO), particulate matters (PM10 and PM2.5), black carbon (BC), organic carbon (OC), volatile organic compounds (VOCs) and ammonia (NH3), in the transport sector of Xiamen, China, during the 2013–2060 period using the Low Emissions Analysis Platform model and quantitative analysis methods. Results show that light-duty vehicles, river boats, buses and heavy-duty trucks are significant common sources of GHG and AP emissions. Road sector abatement during 2013–2020 was most prominent, especially for CO, NO X , VOCs and GHGs. In this sector, guide green travel (GGT) and adjust energy structure (AES) are dominant measures for mitigation synergy between GHGs and APs. From 2021 to 2060, emission pathways for GHGs, SO2, CO, VOCs and NH3 under optimize transport structure (OTS), AES and GGT scenarios will decrease markedly. Their emissions will peak soon relative to those under business as usual scenario. Additionally, the potential of mitigation synergy may mainly be attributed to the road and shipping sectors under AES scenario, which is the most effective in reducing PM10, PM2.5, BC and OC emissions; the mitigation potential under the AES scenario for GHGs and other APs is nearly 1–4 times as high as that under OTS and GGT scenarios. Therefore, mitigation synergy, especially in adjusting the energy structure for the transport sector, is essential for achieving the simultaneous goals of the ‘blue sky’ and ‘carbon peaking and neutrality’.